Overview

Dataset statistics

Number of variables23
Number of observations1929935
Missing cells115638
Missing cells (%)0.3%
Duplicate rows183366
Duplicate rows (%)9.5%
Total size in memory353.4 MiB
Average record size in memory192.0 B

Variable types

Unsupported1
Numeric15
Boolean7

Alerts

Dataset has 183366 (9.5%) duplicate rowsDuplicates
potential_issue is highly imbalanced (99.4%)Imbalance
oe_constraint is highly imbalanced (99.8%)Imbalance
stop_auto_buy is highly imbalanced (77.4%)Imbalance
rev_stop is highly imbalanced (99.5%)Imbalance
went_on_backorder is highly imbalanced (93.8%)Imbalance
lead_time has 115617 (6.0%) missing valuesMissing
national_inv is highly skewed (γ1 = 340.2206342)Skewed
in_transit_qty is highly skewed (γ1 = 168.9800308)Skewed
forecast_3_month is highly skewed (γ1 = 142.7827259)Skewed
forecast_6_month is highly skewed (γ1 = 138.8179394)Skewed
forecast_9_month is highly skewed (γ1 = 142.6836687)Skewed
sales_1_month is highly skewed (γ1 = 193.7199727)Skewed
sales_3_month is highly skewed (γ1 = 141.8139424)Skewed
sales_6_month is highly skewed (γ1 = 138.9269756)Skewed
sales_9_month is highly skewed (γ1 = 135.4356641)Skewed
min_bank is highly skewed (γ1 = 130.9625785)Skewed
pieces_past_due is highly skewed (γ1 = 414.2698848)Skewed
local_bo_qty is highly skewed (γ1 = 149.6208797)Skewed
sku is an unsupported type, check if it needs cleaning or further analysisUnsupported
national_inv has 123076 (6.4%) zerosZeros
in_transit_qty has 1541941 (79.9%) zerosZeros
forecast_3_month has 1347744 (69.8%) zerosZeros
forecast_6_month has 1240252 (64.3%) zerosZeros
forecast_9_month has 1182117 (61.3%) zerosZeros
sales_1_month has 1100061 (57.0%) zerosZeros
sales_3_month has 869086 (45.0%) zerosZeros
sales_6_month has 739645 (38.3%) zerosZeros
sales_9_month has 669802 (34.7%) zerosZeros
min_bank has 997258 (51.7%) zerosZeros
pieces_past_due has 1901631 (98.5%) zerosZeros
perf_6_month_avg has 44675 (2.3%) zerosZeros
perf_12_month_avg has 37885 (2.0%) zerosZeros
local_bo_qty has 1903730 (98.6%) zerosZeros

Reproduction

Analysis started2023-05-09 10:54:24.836197
Analysis finished2023-05-09 10:56:38.155147
Duration2 minutes and 13.32 seconds
Software versionydata-profiling vv4.1.2
Download configurationconfig.json

Variables

sku
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size29.4 MiB

national_inv
Real number (ℝ)

SKEWED  ZEROS 

Distinct15903
Distinct (%)0.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean496.56852
Minimum-27256
Maximum12334404
Zeros123076
Zeros (%)6.4%
Negative6654
Negative (%)0.3%
Memory size29.4 MiB
2023-05-09T16:26:38.228040image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-27256
5-th percentile0
Q14
median15
Q380
95-th percentile924
Maximum12334404
Range12361660
Interquartile range (IQR)76

Descriptive statistics

Standard deviation29573.442
Coefficient of variation (CV)59.555612
Kurtosis131267.42
Mean496.56852
Median Absolute Deviation (MAD)13
Skewness340.22063
Sum9.5834446 × 108
Variance8.7458847 × 108
MonotonicityNot monotonic
2023-05-09T16:26:38.328105image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 123407
 
6.4%
0 123076
 
6.4%
3 103497
 
5.4%
4 79724
 
4.1%
5 67702
 
3.5%
1 67101
 
3.5%
6 58162
 
3.0%
7 53108
 
2.8%
10 52847
 
2.7%
8 45940
 
2.4%
Other values (15893) 1155370
59.9%
ValueCountFrequency (%)
-27256 1
 
< 0.1%
-25414 3
< 0.1%
-22154 3
< 0.1%
-17698 1
 
< 0.1%
-17669 2
< 0.1%
-13491 1
 
< 0.1%
-9925 1
 
< 0.1%
-8230 1
 
< 0.1%
-8170 1
 
< 0.1%
-8130 1
 
< 0.1%
ValueCountFrequency (%)
12334404 1
< 0.1%
12324456 1
< 0.1%
12315072 1
< 0.1%
12309096 1
< 0.1%
12285100 1
< 0.1%
12181612 1
< 0.1%
12166440 1
< 0.1%
12145792 1
< 0.1%
6363276 1
< 0.1%
6352932 1
< 0.1%

lead_time
Real number (ℝ)

Distinct32
Distinct (%)< 0.1%
Missing115617
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean7.8786266
Minimum0
Maximum52
Zeros12026
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:38.416418image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q14
median8
Q39
95-th percentile12
Maximum52
Range52
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.0542125
Coefficient of variation (CV)0.89536069
Kurtosis26.243386
Mean7.8786266
Median Absolute Deviation (MAD)1
Skewness4.556573
Sum14294334
Variance49.761914
MonotonicityNot monotonic
2023-05-09T16:26:38.498829image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
8 780719
40.5%
2 384319
19.9%
12 228997
 
11.9%
4 147045
 
7.6%
9 141423
 
7.3%
52 34418
 
1.8%
3 18602
 
1.0%
10 16248
 
0.8%
0 12026
 
0.6%
14 11820
 
0.6%
Other values (22) 38701
 
2.0%
(Missing) 115617
 
6.0%
ValueCountFrequency (%)
0 12026
 
0.6%
1 24
 
< 0.1%
2 384319
19.9%
3 18602
 
1.0%
4 147045
 
7.6%
5 4609
 
0.2%
6 5826
 
0.3%
7 239
 
< 0.1%
8 780719
40.5%
9 141423
 
7.3%
ValueCountFrequency (%)
52 34418
1.8%
40 56
 
< 0.1%
35 40
 
< 0.1%
30 356
 
< 0.1%
28 96
 
< 0.1%
26 120
 
< 0.1%
25 8
 
< 0.1%
24 148
 
< 0.1%
23 16
 
< 0.1%
22 152
 
< 0.1%

in_transit_qty
Real number (ℝ)

SKEWED  ZEROS 

Distinct5543
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean43.064419
Minimum0
Maximum489408
Zeros1541941
Zeros (%)79.9%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:38.587711image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile66
Maximum489408
Range489408
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1295.4208
Coefficient of variation (CV)30.081001
Kurtosis41191.441
Mean43.064419
Median Absolute Deviation (MAD)0
Skewness168.98003
Sum83111487
Variance1678115.1
MonotonicityNot monotonic
2023-05-09T16:26:38.684213image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1541941
79.9%
1 41250
 
2.1%
2 25128
 
1.3%
3 19506
 
1.0%
4 17436
 
0.9%
5 14608
 
0.8%
6 12907
 
0.7%
10 10109
 
0.5%
8 9932
 
0.5%
7 9209
 
0.5%
Other values (5533) 227908
 
11.8%
ValueCountFrequency (%)
0 1541941
79.9%
1 41250
 
2.1%
2 25128
 
1.3%
3 19506
 
1.0%
4 17436
 
0.9%
5 14608
 
0.8%
6 12907
 
0.7%
7 9209
 
0.5%
8 9932
 
0.5%
9 7179
 
0.4%
ValueCountFrequency (%)
489408 1
< 0.1%
487680 1
< 0.1%
328060 1
< 0.1%
327156 1
< 0.1%
292093 1
< 0.1%
288960 1
< 0.1%
288768 1
< 0.1%
285365 1
< 0.1%
276703 1
< 0.1%
265272 1
< 0.1%

forecast_3_month
Real number (ℝ)

SKEWED  ZEROS 

Distinct8293
Distinct (%)0.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean178.53996
Minimum0
Maximum1510592
Zeros1347744
Zeros (%)69.8%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:38.780190image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile300
Maximum1510592
Range1510592
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5108.7715
Coefficient of variation (CV)28.614163
Kurtosis27297.357
Mean178.53996
Median Absolute Deviation (MAD)0
Skewness142.78273
Sum3.4457033 × 108
Variance26099546
MonotonicityNot monotonic
2023-05-09T16:26:39.148436image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1347744
69.8%
1 35757
 
1.9%
2 29961
 
1.6%
5 22258
 
1.2%
4 21158
 
1.1%
3 18427
 
1.0%
10 16398
 
0.8%
6 15417
 
0.8%
20 12596
 
0.7%
12 12576
 
0.7%
Other values (8283) 397642
 
20.6%
ValueCountFrequency (%)
0 1347744
69.8%
1 35757
 
1.9%
2 29961
 
1.6%
3 18427
 
1.0%
4 21158
 
1.1%
5 22258
 
1.2%
6 15417
 
0.8%
7 9240
 
0.5%
8 11809
 
0.6%
9 7790
 
0.4%
ValueCountFrequency (%)
1510592 1
< 0.1%
1427612 1
< 0.1%
1218328 2
< 0.1%
1126656 1
< 0.1%
1103084 1
< 0.1%
1092576 1
< 0.1%
1058396 1
< 0.1%
1046592 1
< 0.1%
1037228 1
< 0.1%
1021940 1
< 0.1%

forecast_6_month
Real number (ℝ)

SKEWED  ZEROS 

Distinct11788
Distinct (%)0.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean345.46607
Minimum0
Maximum2461360
Zeros1240252
Zeros (%)64.3%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:39.248894image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q312
95-th percentile600
Maximum2461360
Range2461360
Interquartile range (IQR)12

Descriptive statistics

Standard deviation9831.5646
Coefficient of variation (CV)28.458843
Kurtosis25080.966
Mean345.46607
Median Absolute Deviation (MAD)0
Skewness138.81794
Sum6.6672672 × 108
Variance96659663
MonotonicityNot monotonic
2023-05-09T16:26:39.348373image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1240252
64.3%
1 31809
 
1.6%
2 30224
 
1.6%
3 22671
 
1.2%
4 21347
 
1.1%
5 19028
 
1.0%
6 18113
 
0.9%
10 17975
 
0.9%
8 14644
 
0.8%
20 13814
 
0.7%
Other values (11778) 500057
25.9%
ValueCountFrequency (%)
0 1240252
64.3%
1 31809
 
1.6%
2 30224
 
1.6%
3 22671
 
1.2%
4 21347
 
1.1%
5 19028
 
1.0%
6 18113
 
0.9%
7 12868
 
0.7%
8 14644
 
0.8%
9 7656
 
0.4%
ValueCountFrequency (%)
2461360 1
< 0.1%
2446072 1
< 0.1%
2157024 1
< 0.1%
2119148 1
< 0.1%
2109740 1
< 0.1%
2104128 1
< 0.1%
2094452 1
< 0.1%
2094336 1
< 0.1%
2087396 1
< 0.1%
2085044 1
< 0.1%

forecast_9_month
Real number (ℝ)

SKEWED  ZEROS 

Distinct14523
Distinct (%)0.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean506.60701
Minimum0
Maximum3777304
Zeros1182117
Zeros (%)61.3%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:39.442657image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q320
95-th percentile896
Maximum3777304
Range3777304
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14345.435
Coefficient of variation (CV)28.316692
Kurtosis26835.195
Mean506.60701
Median Absolute Deviation (MAD)0
Skewness142.68367
Sum9.777181 × 108
Variance2.0579149 × 108
MonotonicityNot monotonic
2023-05-09T16:26:39.536007image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1182117
61.3%
1 30475
 
1.6%
2 29263
 
1.5%
3 23594
 
1.2%
4 21986
 
1.1%
5 20113
 
1.0%
6 18689
 
1.0%
10 18365
 
1.0%
8 15698
 
0.8%
20 14264
 
0.7%
Other values (14513) 555370
28.8%
ValueCountFrequency (%)
0 1182117
61.3%
1 30475
 
1.6%
2 29263
 
1.5%
3 23594
 
1.2%
4 21986
 
1.1%
5 20113
 
1.0%
6 18689
 
1.0%
7 11748
 
0.6%
8 15698
 
0.8%
9 8974
 
0.5%
ValueCountFrequency (%)
3777304 1
< 0.1%
3760840 1
< 0.1%
3232820 1
< 0.1%
3229292 1
< 0.1%
3206948 1
< 0.1%
3196364 1
< 0.1%
3162260 1
< 0.1%
3158732 1
< 0.1%
3149324 1
< 0.1%
3124704 1
< 0.1%

sales_1_month
Real number (ℝ)

SKEWED  ZEROS 

Distinct6088
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean55.368193
Minimum0
Maximum741774
Zeros1100061
Zeros (%)57.0%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:39.635496image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile106
Maximum741774
Range741774
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1884.3775
Coefficient of variation (CV)34.033574
Kurtosis53099.568
Mean55.368193
Median Absolute Deviation (MAD)0
Skewness193.71997
Sum1.0685696 × 108
Variance3550878.5
MonotonicityNot monotonic
2023-05-09T16:26:39.725724image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1100061
57.0%
1 165508
 
8.6%
2 90068
 
4.7%
3 56397
 
2.9%
4 43288
 
2.2%
5 33820
 
1.8%
6 27013
 
1.4%
7 21695
 
1.1%
8 19426
 
1.0%
10 16603
 
0.9%
Other values (6078) 356055
 
18.4%
ValueCountFrequency (%)
0 1100061
57.0%
1 165508
 
8.6%
2 90068
 
4.7%
3 56397
 
2.9%
4 43288
 
2.2%
5 33820
 
1.8%
6 27013
 
1.4%
7 21695
 
1.1%
8 19426
 
1.0%
9 15957
 
0.8%
ValueCountFrequency (%)
741774 1
< 0.1%
741762 1
< 0.1%
741750 1
< 0.1%
393665 1
< 0.1%
376025 1
< 0.1%
369425 1
< 0.1%
366191 1
< 0.1%
361803 1
< 0.1%
361239 1
< 0.1%
359505 1
< 0.1%

sales_3_month
Real number (ℝ)

SKEWED  ZEROS 

Distinct11149
Distinct (%)0.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean174.66395
Minimum0
Maximum1105478
Zeros869086
Zeros (%)45.0%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:39.828876image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q315
95-th percentile349
Maximum1105478
Range1105478
Interquartile range (IQR)15

Descriptive statistics

Standard deviation5188.8572
Coefficient of variation (CV)29.70766
Kurtosis24391.249
Mean174.66395
Median Absolute Deviation (MAD)1
Skewness141.81394
Sum3.3708989 × 108
Variance26924239
MonotonicityNot monotonic
2023-05-09T16:26:39.921521image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 869086
45.0%
1 156660
 
8.1%
2 92910
 
4.8%
3 60714
 
3.1%
4 47486
 
2.5%
5 39014
 
2.0%
6 31848
 
1.7%
7 26572
 
1.4%
8 23870
 
1.2%
10 20385
 
1.1%
Other values (11139) 561389
29.1%
ValueCountFrequency (%)
0 869086
45.0%
1 156660
 
8.1%
2 92910
 
4.8%
3 60714
 
3.1%
4 47486
 
2.5%
5 39014
 
2.0%
6 31848
 
1.7%
7 26572
 
1.4%
8 23870
 
1.2%
9 20120
 
1.0%
ValueCountFrequency (%)
1105478 1
< 0.1%
1104181 1
< 0.1%
1100523 1
< 0.1%
1099852 1
< 0.1%
1094112 1
< 0.1%
1091281 1
< 0.1%
1086554 1
< 0.1%
1084974 1
< 0.1%
1081560 1
< 0.1%
1076623 1
< 0.1%

sales_6_month
Real number (ℝ)

SKEWED  ZEROS 

Distinct15813
Distinct (%)0.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean341.56553
Minimum0
Maximum2146625
Zeros739645
Zeros (%)38.3%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:40.020501image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q331
95-th percentile696
Maximum2146625
Range2146625
Interquartile range (IQR)31

Descriptive statistics

Standard deviation9585.0329
Coefficient of variation (CV)28.062062
Kurtosis24221.359
Mean341.56553
Median Absolute Deviation (MAD)2
Skewness138.92698
Sum6.5919892 × 108
Variance91872855
MonotonicityNot monotonic
2023-05-09T16:26:40.109701image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 739645
38.3%
1 145503
 
7.5%
2 90790
 
4.7%
3 60480
 
3.1%
4 47719
 
2.5%
5 39089
 
2.0%
6 32346
 
1.7%
7 26582
 
1.4%
8 24163
 
1.3%
9 21058
 
1.1%
Other values (15803) 702559
36.4%
ValueCountFrequency (%)
0 739645
38.3%
1 145503
 
7.5%
2 90790
 
4.7%
3 60480
 
3.1%
4 47719
 
2.5%
5 39089
 
2.0%
6 32346
 
1.7%
7 26582
 
1.4%
8 24163
 
1.3%
9 21058
 
1.1%
ValueCountFrequency (%)
2146625 1
< 0.1%
2145715 1
< 0.1%
2133557 1
< 0.1%
2123946 1
< 0.1%
2117803 1
< 0.1%
2113901 1
< 0.1%
2112231 1
< 0.1%
2103389 1
< 0.1%
2098852 1
< 0.1%
2086531 1
< 0.1%

sales_9_month
Real number (ℝ)

SKEWED  ZEROS 

Distinct19581
Distinct (%)1.0%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean523.57736
Minimum0
Maximum3205172
Zeros669802
Zeros (%)34.7%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:40.202786image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q347
95-th percentile1060
Maximum3205172
Range3205172
Interquartile range (IQR)47

Descriptive statistics

Standard deviation14733.269
Coefficient of variation (CV)28.139623
Kurtosis23014.498
Mean523.57736
Median Absolute Deviation (MAD)4
Skewness135.43566
Sum1.0104698 × 109
Variance2.1706923 × 108
MonotonicityNot monotonic
2023-05-09T16:26:40.293725image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 669802
34.7%
1 137677
 
7.1%
2 87472
 
4.5%
3 59780
 
3.1%
4 47281
 
2.4%
5 39393
 
2.0%
6 32742
 
1.7%
7 26897
 
1.4%
8 24198
 
1.3%
9 21475
 
1.1%
Other values (19571) 783217
40.6%
ValueCountFrequency (%)
0 669802
34.7%
1 137677
 
7.1%
2 87472
 
4.5%
3 59780
 
3.1%
4 47281
 
2.4%
5 39393
 
2.0%
6 32742
 
1.7%
7 26897
 
1.4%
8 24198
 
1.3%
9 21475
 
1.1%
ValueCountFrequency (%)
3205172 1
< 0.1%
3204929 1
< 0.1%
3201035 1
< 0.1%
3197338 1
< 0.1%
3195211 1
< 0.1%
3182148 1
< 0.1%
3167394 1
< 0.1%
3163794 1
< 0.1%
3120875 1
< 0.1%
3119450 1
< 0.1%

min_bank
Real number (ℝ)

SKEWED  ZEROS 

Distinct5909
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean52.776393
Minimum0
Maximum313319
Zeros997258
Zeros (%)51.7%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:40.392573image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile125
Maximum313319
Range313319
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1257.9686
Coefficient of variation (CV)23.835819
Kurtosis23388.382
Mean52.776393
Median Absolute Deviation (MAD)0
Skewness130.96258
Sum1.0185496 × 108
Variance1582485
MonotonicityNot monotonic
2023-05-09T16:26:40.481115image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 997258
51.7%
1 287930
 
14.9%
2 129167
 
6.7%
3 41408
 
2.1%
4 25511
 
1.3%
5 18360
 
1.0%
6 13865
 
0.7%
7 11042
 
0.6%
8 9010
 
0.5%
15 8422
 
0.4%
Other values (5899) 387961
 
20.1%
ValueCountFrequency (%)
0 997258
51.7%
1 287930
 
14.9%
2 129167
 
6.7%
3 41408
 
2.1%
4 25511
 
1.3%
5 18360
 
1.0%
6 13865
 
0.7%
7 11042
 
0.6%
8 9010
 
0.5%
9 7035
 
0.4%
ValueCountFrequency (%)
313319 1
< 0.1%
311423 1
< 0.1%
310427 1
< 0.1%
309667 1
< 0.1%
308055 1
< 0.1%
307627 1
< 0.1%
303713 1
< 0.1%
291059 1
< 0.1%
205786 1
< 0.1%
204803 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size18.4 MiB
False
1928945 
True
 
989
(Missing)
 
1
ValueCountFrequency (%)
False 1928945
99.9%
True 989
 
0.1%
(Missing) 1
 
< 0.1%
2023-05-09T16:26:40.583165image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

pieces_past_due
Real number (ℝ)

SKEWED  ZEROS 

Distinct874
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0161943
Minimum0
Maximum146496
Zeros1901631
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:40.660375image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum146496
Range146496
Interquartile range (IQR)0

Descriptive statistics

Standard deviation229.6113
Coefficient of variation (CV)113.88352
Kurtosis210414.07
Mean2.0161943
Median Absolute Deviation (MAD)0
Skewness414.26988
Sum3891122
Variance52721.35
MonotonicityNot monotonic
2023-05-09T16:26:40.749595image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1901631
98.5%
1 4350
 
0.2%
2 2406
 
0.1%
4 1395
 
0.1%
3 1357
 
0.1%
5 1184
 
0.1%
6 923
 
< 0.1%
12 855
 
< 0.1%
10 841
 
< 0.1%
8 691
 
< 0.1%
Other values (864) 14301
 
0.7%
ValueCountFrequency (%)
0 1901631
98.5%
1 4350
 
0.2%
2 2406
 
0.1%
3 1357
 
0.1%
4 1395
 
0.1%
5 1184
 
0.1%
6 923
 
< 0.1%
7 550
 
< 0.1%
8 691
 
< 0.1%
9 431
 
< 0.1%
ValueCountFrequency (%)
146496 1
< 0.1%
137625 1
< 0.1%
98776 1
< 0.1%
87689 1
< 0.1%
83600 1
< 0.1%
79964 1
< 0.1%
74084 1
< 0.1%
61144 1
< 0.1%
59136 1
< 0.1%
36452 1
< 0.1%

perf_6_month_avg
Real number (ℝ)

Distinct102
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-6.8998218
Minimum-99
Maximum1
Zeros44675
Zeros (%)2.3%
Negative148578
Negative (%)7.7%
Memory size29.4 MiB
2023-05-09T16:26:40.849935image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-99
5-th percentile-99
Q10.63
median0.82
Q30.96
95-th percentile1
Maximum1
Range100
Interquartile range (IQR)0.33

Descriptive statistics

Standard deviation26.599803
Coefficient of variation (CV)-3.8551435
Kurtosis8.0712063
Mean-6.8998218
Median Absolute Deviation (MAD)0.15
Skewness-3.1733535
Sum-13316201
Variance707.54953
MonotonicityNot monotonic
2023-05-09T16:26:40.946957image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.99 163323
 
8.5%
1 150339
 
7.8%
-99 148578
 
7.7%
0.73 128818
 
6.7%
0.98 97390
 
5.0%
0.97 71120
 
3.7%
0.95 50482
 
2.6%
0.78 49056
 
2.5%
0.82 46602
 
2.4%
0 44675
 
2.3%
Other values (92) 979551
50.8%
ValueCountFrequency (%)
-99 148578
7.7%
0 44675
 
2.3%
0.01 648
 
< 0.1%
0.02 1156
 
0.1%
0.03 829
 
< 0.1%
0.04 724
 
< 0.1%
0.05 1352
 
0.1%
0.06 1393
 
0.1%
0.07 2569
 
0.1%
0.08 1947
 
0.1%
ValueCountFrequency (%)
1 150339
7.8%
0.99 163323
8.5%
0.98 97390
5.0%
0.97 71120
3.7%
0.96 44116
 
2.3%
0.95 50482
 
2.6%
0.94 43978
 
2.3%
0.93 39878
 
2.1%
0.92 25924
 
1.3%
0.91 33770
 
1.7%

perf_12_month_avg
Real number (ℝ)

Distinct102
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-6.462295
Minimum-99
Maximum1
Zeros37885
Zeros (%)2.0%
Negative140024
Negative (%)7.3%
Memory size29.4 MiB
2023-05-09T16:26:41.039924image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-99
5-th percentile-99
Q10.66
median0.81
Q30.95
95-th percentile0.99
Maximum1
Range100
Interquartile range (IQR)0.29

Descriptive statistics

Standard deviation25.88335
Coefficient of variation (CV)-4.0052875
Kurtosis8.8594215
Mean-6.462295
Median Absolute Deviation (MAD)0.15
Skewness-3.2951974
Sum-12471803
Variance669.94779
MonotonicityNot monotonic
2023-05-09T16:26:41.138350image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.99 152682
 
7.9%
-99 140024
 
7.3%
0.78 131353
 
6.8%
0.98 106119
 
5.5%
0.97 74113
 
3.8%
0.96 72752
 
3.8%
0.66 61831
 
3.2%
0.9 53203
 
2.8%
0.95 53112
 
2.8%
1 50443
 
2.6%
Other values (92) 1034302
53.6%
ValueCountFrequency (%)
-99 140024
7.3%
0 37885
 
2.0%
0.01 2814
 
0.1%
0.02 437
 
< 0.1%
0.03 639
 
< 0.1%
0.04 1179
 
0.1%
0.05 743
 
< 0.1%
0.06 873
 
< 0.1%
0.07 1193
 
0.1%
0.08 1720
 
0.1%
ValueCountFrequency (%)
1 50443
 
2.6%
0.99 152682
7.9%
0.98 106119
5.5%
0.97 74113
3.8%
0.96 72752
3.8%
0.95 53112
 
2.8%
0.94 43409
 
2.2%
0.93 35577
 
1.8%
0.92 35805
 
1.9%
0.91 34296
 
1.8%

local_bo_qty
Real number (ℝ)

SKEWED  ZEROS 

Distinct686
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.65370422
Minimum0
Maximum12530
Zeros1903730
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size29.4 MiB
2023-05-09T16:26:41.230702image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum12530
Range12530
Interquartile range (IQR)0

Descriptive statistics

Standard deviation35.432305
Coefficient of variation (CV)54.20235
Kurtosis30837.955
Mean0.65370422
Median Absolute Deviation (MAD)0
Skewness149.62088
Sum1261606
Variance1255.4482
MonotonicityNot monotonic
2023-05-09T16:26:41.327561image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1903730
98.6%
1 8055
 
0.4%
2 3332
 
0.2%
3 1930
 
0.1%
4 1381
 
0.1%
5 1098
 
0.1%
6 756
 
< 0.1%
7 621
 
< 0.1%
10 566
 
< 0.1%
8 501
 
< 0.1%
Other values (676) 7964
 
0.4%
ValueCountFrequency (%)
0 1903730
98.6%
1 8055
 
0.4%
2 3332
 
0.2%
3 1930
 
0.1%
4 1381
 
0.1%
5 1098
 
0.1%
6 756
 
< 0.1%
7 621
 
< 0.1%
8 501
 
< 0.1%
9 382
 
< 0.1%
ValueCountFrequency (%)
12530 1
< 0.1%
10045 1
< 0.1%
10024 1
< 0.1%
8600 1
< 0.1%
7812 1
< 0.1%
7048 1
< 0.1%
7000 1
< 0.1%
6965 1
< 0.1%
6955 1
< 0.1%
6732 1
< 0.1%

deck_risk
Boolean

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size18.4 MiB
False
1494481 
True
435453 
(Missing)
 
1
ValueCountFrequency (%)
False 1494481
77.4%
True 435453
 
22.6%
(Missing) 1
 
< 0.1%
2023-05-09T16:26:41.421168image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size18.4 MiB
False
1929642 
True
 
292
(Missing)
 
1
ValueCountFrequency (%)
False 1929642
> 99.9%
True 292
 
< 0.1%
(Missing) 1
 
< 0.1%
2023-05-09T16:26:41.495337image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

ppap_risk
Boolean

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size18.4 MiB
False
1697382 
True
232552 
(Missing)
 
1
ValueCountFrequency (%)
False 1697382
88.0%
True 232552
 
12.0%
(Missing) 1
 
< 0.1%
2023-05-09T16:26:41.567540image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size18.4 MiB
True
1859390 
False
 
70544
(Missing)
 
1
ValueCountFrequency (%)
True 1859390
96.3%
False 70544
 
3.7%
(Missing) 1
 
< 0.1%
2023-05-09T16:26:41.642671image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

rev_stop
Boolean

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size18.4 MiB
False
1929095 
True
 
839
(Missing)
 
1
ValueCountFrequency (%)
False 1929095
> 99.9%
True 839
 
< 0.1%
(Missing) 1
 
< 0.1%
2023-05-09T16:26:41.716416image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size18.4 MiB
False
1915953 
True
 
13981
(Missing)
 
1
ValueCountFrequency (%)
False 1915953
99.3%
True 13981
 
0.7%
(Missing) 1
 
< 0.1%
2023-05-09T16:26:41.788453image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Interactions

2023-05-09T16:26:17.795346image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:04.659607image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:09.940146image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:14.961066image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:20.155826image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:25.275296image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:30.693928image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:36.150725image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:41.387261image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:46.510479image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:51.809191image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:56.939050image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:02.126732image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:07.590720image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:12.716498image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:18.121550image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:04.989176image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:10.265062image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:15.276912image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:20.482322image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:25.604359image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:31.035607image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:36.473447image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:41.711854image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:46.853978image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:52.130035image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:57.272433image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:02.456275image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:07.931054image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:13.041440image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:18.463319image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:05.331011image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:10.602617image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:15.599338image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:20.828324image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:25.952814image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:31.555862image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:36.818038image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:42.050509image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:47.383941image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:52.467614image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:57.614125image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:02.798207image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:08.262075image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:13.395577image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:18.805366image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:05.661088image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:10.939284image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:15.938317image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:21.164716image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:26.293540image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:31.920368image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:37.166743image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:42.388585image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:47.734265image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:52.810084image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:57.959056image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:03.150379image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:08.599970image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:13.729706image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:19.147983image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:06.005105image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:11.268617image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:16.281122image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:21.515687image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:26.648942image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:32.289999image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:37.511441image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:42.744198image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:48.084648image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:53.155627image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:58.312349image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:03.502361image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:08.948802image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:14.066735image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:19.489878image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:06.352782image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:11.609777image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:16.622305image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:21.851914image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:27.009638image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:32.644598image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:37.866842image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:43.087746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:48.421089image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:53.492793image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:58.653372image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:03.839692image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:09.287229image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:14.401353image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:19.834389image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:06.715838image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:11.956765image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:16.976354image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:22.193473image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:27.370404image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:33.003866image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:38.203383image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:43.433113image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:48.763844image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:53.839267image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:59.002614image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:04.187479image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:09.641134image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:14.750181image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:20.178349image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:07.054278image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:12.296873image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:17.313972image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:22.537519image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:27.737165image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:33.355839image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:38.557430image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:43.769080image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:49.100221image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:54.192297image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:59.368798image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:04.538060image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:09.991700image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:15.098375image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:20.510885image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:07.413050image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:12.628088image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:17.648364image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:22.880237image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:28.119073image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:33.701532image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:38.918604image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:44.104953image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:49.419895image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:54.534587image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:59.716033image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:04.884394image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:10.330048image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:15.432268image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:20.852363image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:07.758933image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:12.963497image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:17.980893image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:23.216480image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:28.464856image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:34.040409image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:39.279821image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:44.438979image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:49.755609image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:54.870624image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:00.057906image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:05.235099image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:10.665519image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:15.772793image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:21.199785image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:08.102889image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:13.298358image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:18.324726image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:23.559797image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:28.845884image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:34.399538image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:39.657745image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:44.783404image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:50.096394image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:55.213492image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:00.395110image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:05.595992image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:11.003291image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:16.122450image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:21.545858image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:08.444803image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:13.632517image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:18.792043image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:23.906932image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:29.221284image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:34.746342image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:40.007572image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:45.122425image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:50.450899image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:55.556393image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:00.749552image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:05.930457image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:11.348548image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:16.454149image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:21.891657image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:08.896639image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:13.965320image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:19.138268image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:24.246270image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:29.589092image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:35.112350image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:40.351362image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:45.473429image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:50.795646image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:55.908367image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:01.094066image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:06.286291image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:11.694646image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:16.796750image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:22.226774image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:09.246197image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:14.305280image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:19.477023image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:24.586277image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:29.952661image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:35.449509image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:40.702230image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:45.816981image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:51.129551image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:56.247584image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:01.431035image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:06.865854image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:12.033314image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:17.128742image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:22.561448image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:09.587858image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:14.636262image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:19.818342image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:24.936328image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:30.316367image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:35.807034image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:41.044968image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:46.162610image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:51.468181image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:25:56.593759image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:01.767089image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:07.224851image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:12.372990image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-09T16:26:17.462128image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Missing values

2023-05-09T16:26:23.951701image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-05-09T16:26:26.890715image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-05-09T16:26:35.025879image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

skunational_invlead_timein_transit_qtyforecast_3_monthforecast_6_monthforecast_9_monthsales_1_monthsales_3_monthsales_6_monthsales_9_monthmin_bankpotential_issuepieces_past_dueperf_6_month_avgperf_12_month_avglocal_bo_qtydeck_riskoe_constraintppap_riskstop_auto_buyrev_stopwent_on_backorder
010268270.0NaN0.00.00.00.00.00.00.00.00.0No0.0-99.00-99.000.0NoNoNoYesNoNo
110433842.09.00.00.00.00.00.00.00.00.00.0No0.00.990.990.0NoNoNoYesNoNo
210436962.0NaN0.00.00.00.00.00.00.00.00.0No0.0-99.00-99.000.0YesNoNoYesNoNo
310438527.08.00.00.00.00.00.00.00.00.01.0No0.00.100.130.0NoNoNoYesNoNo
410440488.0NaN0.00.00.00.00.00.00.04.02.0No0.0-99.00-99.000.0YesNoNoYesNoNo
5104419813.08.00.00.00.00.00.00.00.00.00.0No0.00.820.870.0NoNoNoYesNoNo
610446431095.0NaN0.00.00.00.00.00.00.00.04.0No0.0-99.00-99.000.0YesNoNoYesNoNo
710450986.02.00.00.00.00.00.00.00.00.00.0No0.00.000.000.0YesNoYesYesNoNo
81045815140.0NaN0.015.0114.0152.00.00.00.00.00.0No0.0-99.00-99.000.0NoNoNoYesNoNo
910458674.08.00.00.00.00.00.00.00.00.00.0No0.00.820.870.0NoNoNoYesNoNo
skunational_invlead_timein_transit_qtyforecast_3_monthforecast_6_monthforecast_9_monthsales_1_monthsales_3_monthsales_6_monthsales_9_monthmin_bankpotential_issuepieces_past_dueperf_6_month_avgperf_12_month_avglocal_bo_qtydeck_riskoe_constraintppap_riskstop_auto_buyrev_stopwent_on_backorder
242065352698220.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoNoYesNoNo
242066352698350.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoYesYesNoNo
242067352698420.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoNoYesNoNo
2420683526985165.0NaN0.056.0180.0273.021.086.0215.0314.040.0No0.0-99.00-99.000.0NoNoNoYesNoNo
242069352698611.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoNoYesNoNo
242070352698712.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoNoYesNoNo
242071352698813.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoNoYesNoNo
242072352698913.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoNoYesNoNo
242073352699010.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoNoYesNoNo
24207435269912913.012.00.00.00.00.00.030.088.088.04.0No0.00.480.480.0YesNoNoYesNoNo

Duplicate rows

Most frequently occurring

national_invlead_timein_transit_qtyforecast_3_monthforecast_6_monthforecast_9_monthsales_1_monthsales_3_monthsales_6_monthsales_9_monthmin_bankpotential_issuepieces_past_dueperf_6_month_avgperf_12_month_avglocal_bo_qtydeck_riskoe_constraintppap_riskstop_auto_buyrev_stopwent_on_backorder# duplicates
134400.0NaN0.00.00.00.00.00.00.00.00.0No0.0-99.00-99.000.0NoNoNoYesNoNo7893
9949613.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoNoYesNoNo3792
302312.012.00.00.00.00.00.00.00.00.00.0No0.00.730.790.0NoNoNoYesNoNo3254
236032.04.00.00.00.00.00.00.00.00.00.0No0.00.730.780.0NoNoNoYesNoNo3178
302512.012.00.00.00.00.00.00.00.00.00.0No0.00.780.780.0NoNoNoYesNoNo3140
8733710.012.00.00.00.00.00.00.00.00.01.0No0.00.480.480.0YesNoNoYesNoNo3036
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408103.012.00.00.00.00.00.00.00.00.00.0No0.00.570.680.0NoNoNoYesNoNo2199